Purpose

Background

Atrial fibrillation (AF) is the most common cardiac arrhythmia, characterized by chaotic electrical activation and contraction of the atria. AF is a serious condition linked with increased morbidity and mortality, in particular due to stroke caused by abnormal atrial hemodynamics, and increased risk of heart failure and ventricular arrhythmia. This epidemic currently affects more than 6 million Europeans, a figure that will double by 2050. At least 1% of the healthcare budget of European countries is currently spent on AF; annual costs are estimated at € 13.5 billion.

AF is a progressive disease. Over time, AF episodes become more frequent and have longer duration. For many patients, the paroxysmal AF becomes persistent, leading to more severe symptoms and increased risk for comorbidities among patients. In these patients drugs are often completely ineffective.

Clinical challenge

Atrial ablation, an invasive procedure during which small areas of myocardial tissue are destroyed to block abnormal signals, is an effective treatment for AF patients. However, for those with persistent (AF that lasts more than >7 days) or longstanding persistent AF (AF that lasts longer than >1 year), trigger points may exist in many areas of the atria, and AF will frequently recur following ablation therapy. Efficacy of the first ablation has been reported in the range 30%-75%[1][2]; and, thus, multiple procedures are often needed. Catheter ablation procedures may be very time consuming and expensive, increasing cost and ultimate risks for the patient[3]. The loss of conductive and contractile tissue following ablation adversely affects atrial mechanical function, further increasing the risk of stroke. In cases of high AF recurrence risk, the patient may need lifelong therapy with anti-coagulants to reduce stroke risk, also implying severe side effects.

Unfortunately, there is no standard strategy to remediate persistent AF: the ablation sequence used depends on the individual electrophysiologist. Few electrophysiologists can conduct clinical trials on specific ablation strategies or lesion sets and instead rely on what has worked in their experience Results from trials are also often not directly comparable, due to differences in follow-up and monitoring. Further complicating ablation treatment strategy is that in patients that may benefit from ablation, efficacy is significantly increased if the procedure is performed as early as possible.

Therefore understanding whether and when ablation is likely to benefit a particular patient, and whether AF is likely to recur, will decrease the risk for disease progression and patient morbidity and mortality, maximize positive outcomes and ensure judicious resource allocation in our healthcare systems. Currently there are no decision support tools available, enabling clinicians to access integrated AF patient data together with predictive models to facilitate risk stratification and subsequent treatment planning.

Objective

There is a great demand for a clinical decision support tool integrating traditional patient data streams together with the emerging methodologies of the patient-specific predictive model and genetic profiling. The overall ambition of SysAFib is to integrate existing tools and related datasets presently at our disposal to build and validate a clinical decision support system (DSS) for AF therapy planning. Specifically, the system will provide important support for clinicians to determine whether ablation is the right treatment for the patient in question, and, if ablation is performed, if the AF is likely to recur. We hypothesize that provision of unique information, including patient-specific biophysical (computational) models, via a DSS for clinical decision making for ablation therapy for AF management will result in (a) more timely and (b) more appropriate patient selection as evidenced by follow-up clinician survey, patient outcomes, and proof-of-concept clinical trial.